This invention relates generally to imaging systems, and more particularly, to calibration of a medical imaging system.
In at least some known imaging systems, a radiation source projects a cone-shaped beam which passes through the object being imaged, such as a patient and impinges upon an array of radiation detectors. In some known tomosynthesis systems, the radiation source rotates with a gantry around a pivot point, and views of the object are acquired for different projection angles. As used herein xe2x80x9cviewxe2x80x9d refers to a single projection image or, more particularly, xe2x80x9cviewxe2x80x9d refers to a single projection radiograph which forms a projection image. Also, as used herein, a single reconstructed (cross-sectional) image, representative of the structures within the imaged object at a fixed height above the detector, is referred to as a xe2x80x9cslicexe2x80x9d. And a collection (or plurality) of views is referred to as a xe2x80x9cprojection dataset.xe2x80x9d A collection of (or a plurality of) slices for all heights is referred to as a xe2x80x9cthree-dimensional datasetxe2x80x9d representative of an imaged object.
One known method of reconstructing a three-dimensional dataset representative of an imaged object is known in the art as simple backprojection, or shift-and-add. Simple backprojection backprojects each view across the imaged volume, and averages the backprojected views. A xe2x80x9cslicexe2x80x9d of the reconstructed dataset includes the average of the backprojected images for some considered height above the detector. Each slice is representative of the structures of the imaged object at the considered height, and the collection of these slices for different heights, constitutes a three-dimensional dataset representative of the imaged object. Alternatively, in a two-dimensional scan, such as, for example, a Cranio-caudal scan (CC scan) or a mediolateral-oblique scan (MLO), only a single slice is acquired constituting a two-dimensional dataset representative of the imaged object.
In at least one known imaging system, highly attenuating regions of a breast appear brighter than less attenuating regions of the breast. However, deriving a mathematical relationship between specific tissue composition and each individual detector pixel""s photon count is usually complicated by the physics of the imaging chain. Due to these complications, a quantitative tissue composition measurement, although theoretically possible, is rarely performed in mainstream medicine.
A method for estimating a material composition of an imaged object using an imaging system is provided. The imaging system includes a radiation source and a digital detector. The method also includes scanning a plurality of calibration phantoms with varying material composition to acquire a plurality of reference calibration images, estimating an attenuation coefficient thickness product for each pixel in the reference calibration images and estimating a material composition of a region of interest using the estimated pixelwise coefficient thickness product.
A medical imaging system for estimating a material composition of an imaged object is provided. The medical imaging system includes a radiation source and a digital detector, and a computer coupled to the radiation source and the digital detector. The computer is configured to scan a plurality of calibration phantoms with varying material composition to acquire a plurality of reference calibration images, estimate an attenuation coefficient thickness product for each pixel in the reference calibration images, and estimate a material composition of a region of interest using the estimated coefficient thickness product.
A computer readable medium encoded with a program executable by a computer for estimating a material composition of an imaged object is provided. The program is configured to instruct the computer to scan a plurality of calibration phantoms with varying material composition to acquire a plurality of reference calibration images, estimate an attenuation coefficient thickness product for each pixel in the reference calibration images, and estimate a material composition of a region of interest using the estimated coefficient thickness product.